R: Classify a chunk of raster data using multicores

.sits_classify_multicores {sits} | R Documentation

## Classify a chunk of raster data using multicores

### Description

Classifies a block of data using multicores. It breaks the data into horizontal blocks and divides them between the available cores.

Reads data using terra, cleans the data for NAs and missing values. The clean data is stored in a data table with the time instances for all pixels of the block. The algorithm then classifies data on an year by year basis. For each year, extracts the sub-blocks for each band.

After all cores process their blocks, it joins the result and then writes it in the classified images for each corresponding year.

### Usage

    .sits_classify_multicores(
      tile,
      ml_model,
      roi,
      filter_fn,
      impute_fn,
      interp_fn,
      compose_fn,
      memsize,
      multicores,
      output_dir,
      version,
      verbose
    )

### Arguments

`tile` | a single tile of a data cube.
`ml_model` | model trained by `sits_train`.
`roi` | region of interest
`filter_fn` | smoothing filter function to be applied to the data.
`impute_fn` | impute function to replace NA
`interp_fn` | function to interpolate points from cube to match samples
`compose_fn` | function to compose points from cube to match samples
`memsize` | memory available for classification (in GB).
`multicores` | number of cores.
`output_dir` | output directory
`version` | version of result
`verbose` | print processing information?

### Value

List of the classified raster layers.

### Author(s)

Rolf Simoes, rolf.simoes@inpe.br

Gilberto Camara, gilberto.camara@inpe.br

[Package sits version 0.13.0 Index]